Rs10045697-related SNP (Single Nucleotide Polymorphism) marker combination for predicting high myopia risk and susceptibility based on equivalent spherical mirror and application of rs10045697-related SNP marker combination

Abstract

The invention provides an rs10045697 related SNP (Single Nucleotide Polymorphism) marker combination for predicting high myopia risk and susceptibility based on an equivalent spherical mirror and application of the rs10045697 related SNP marker combination, and relates to the field of biological medicines. Specifically, a key SNP marker rs10045697 and a plurality of SNP loci related to high myopia are screened based on equivalent spherical power in a high myopia queue through genome-wide association study (GWAS), and a model constructed based on the SNP marker combination can realize risk stratification and susceptibility detection of high myopia. The method is suitable for ophthalmology screening, high-risk group identification and accurate prevention and control intervention, and has important clinical transformation value.

Description

Technical Field

[0001] This invention relates to the field of biomedicine, specifically to a combination of rs10045697-related SNP markers for predicting the risk and susceptibility to high myopia based on equivalent spherical lenses and their application. Background Technology

[0002] High myopia (HM) has become a major cause of irreversible visual impairment. In the Chinese population, its genetic basis is complex and not yet fully understood. Currently, clinically, a spherical refractive error of -6.00D or lower, or an axial length exceeding 26 mm, is generally used as the diagnostic criteria for high myopia. High myopia is not simply a vision problem; it is closely related to various serious vision-threatening fundus complications, such as myopic choroidal neovascularization (mCNV), retinal detachment (RD), and myopic macular degeneration (MMD). These complications can ultimately lead to irreversible blindness, severely impacting the patient's quality of life.

[0003] Of particular concern is the rapidly increasing prevalence of high myopia among adolescents aged 16-18. It is predicted that the prevalence of high myopia in this group will surge from 7.3% in 2001 to 22.1% in 2050. However, high myopia is extremely complex, and its heterogeneity makes it difficult to accurately define using simple classification diagnostic labels, highlighting the critical technical problem of a severe lack of specific risk biomarkers for high myopia. Existing biomarkers are limited in number, have weak effects, and poor population universality; there are currently no reliable and widely applicable biological or genetic indicators for early identification of high-risk individuals in clinical practice. This lack of risk biomarkers leads to delayed prevention strategies, ambiguous diagnostic criteria, and difficulties in implementing individualized treatment for high myopia, significantly hindering the advancement of precision medicine in this field. Therefore, systematically discovering, validating, and integrating novel high myopia risk biomarkers is not only a key breakthrough in understanding its complex etiology but also an urgent need to achieve early screening, early diagnosis, and precise intervention. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a combination of rs10045697-related SNP markers for predicting the risk and susceptibility to high myopia based on equivalent spherical lenses and their applications.

[0005] To achieve the above-mentioned objectives, the present invention provides the following technical solution: The first aspect of the present invention provides a kit for detecting the risk and susceptibility to high myopia, the kit comprising reagents for detecting SNP locus genotypes, wherein the SNP locus genotypes are rs10045697: C>T, rs72658579: T>C, rs61729970: C>T, rs147091881: G>A, rs12030: T>C, rs78587889: G>A, rs144389163: A>G, rs62621412: G>C, rs59454556: A>C, rs10489177: T>G, rs9787172: C>T, rs77113266: T>A, rs147 783371: G>A, rs2028382: A>C, rs11568351: G>C, rs117179004: G>A, rs4067 :A>G, rs2279321: G>A, rs2279322: C>T, rs544122500: G>A, rs78263747: C> A. rs139530035: G>A, rs17740066: G>A, rs1062293: A>G, rs78351985: A>G, rs9379657: G>A, rs78611987: T>C, rs9473132: G>A, rs9395287: G>A, rs344 60237: G>A, rs146553037: G>T, rs195843: T>C, rs195812: G>T, rs73046334 : T>C, rs6888: A>G, rs2286206: T>C, rs12671595: C>T, rs17214: A>C, rs115 50100: T>C, rs74548386: A>G, rs1832313: C>T, rs1974081: A>G, rs1715859 4: A>C, rs185112369: C>T, rs35083184: A>T, rs12799381: G>A, rs622082: A >G, rs546382: C>T, rs488792: T>G, rs568862: A>G, rs10793024: A>T, rs229 8573: T>C, rs17860556: G>A, rs1356428: A>T, rs143519923: G>A, rs764155 76: G>A, rs79983883: C>A, rs45613639: A>G, rs17015438: T>G, rs2468245: C>T, rs45468703: T>C, rs2468222: G>A, rs34623199: G>A, rs78569455: G>C,rs798792: C>A, rs60214396: C>T, rs199816463: A>G, rs190278786: C>T, rs8 87387: T>C, rs11567842: A>G, rs3736238: C>T, rs758596: G>A, rs55880609: G >A, rs3744003: C>T, rs3753: T>C, rs7230037: G>A, rs572634: A>C, rs230301 4: Combination of A>G, rs471979: G>C, rs6135048: C>A, rs1051415: C>T, rs2747565: G>A. ,

[0006] In this invention, the term "kit" includes reagents for detecting the genotype of the SNP loci described in the first aspect of the invention, and one or more substances selected from the group consisting of: containers, instructions for use, positive controls, negative controls, buffers, auxiliaries, or solvents. Components of the kit may be packaged in an aqueous medium or in lyophilized form. Suitable containers in the kit typically include at least one vial, test tube, long-necked flask, PET bottle, syringe, or other container in which one component can be placed, and preferably appropriately aliquoted. When more than one component is present in the kit, the kit will also typically include a second, third, or other additional container in which the additional components are placed separately. However, different combinations of components may be contained in a single vial. The kit of the present invention will also typically include a container for containing the reactants, sealed for commercial sale. Such a container may include injection-molded or blow-molded plastic containers in which the desired vials can be held.

[0007] In some embodiments, the reagents include those used to detect the SNP locus genotype by TaqMan probe assay, sequencing, microarray assay, mass spectrometry by flight, restriction fragment length polymorphism assay, single strand conformation polymorphism assay, allele-specific PCR, SNaPshot assay, SNPlex assay, denaturing high performance liquid chromatography, or denaturing gradient gel electrophoresis.

[0008] In some embodiments, the kit includes probes or primers.

[0009] In some embodiments, the kit may further include one or more of the following: reagents for collecting and processing subject samples, standards, calibrators, buffer solutions, and instructions.

[0010] The second aspect of the present invention provides the application of a reagent for detecting the SNP locus genotype described in the first aspect in a sample to be tested in the preparation of a product for assessing the risk of high myopia, the product comprising a reagent kit, a chip, a nucleic acid membrane strip, a system, an apparatus, and a storage medium.

[0011] In this invention, the product may comprise a solid substrate such as a chip, a glass slide, an array, etc., having reagents capable of detecting one or more blood biomarkers or other sample-derived biomarkers fixed at predetermined locations on the substrate. As an illustrative example, reagents fixed at discrete predetermined locations may be provided to the chip for detecting the genotype of SNP biomarkers in a blood sample, their concentration in any quantity or any combination thereof.

[0012] The term "chip," also known as an "array," refers to a solid support containing linked nucleic acid or peptide probes. An array typically contains a variety of different nucleic acid or peptide probes attached to a substrate surface at different known locations. Arrays can contain flat surfaces or can be nucleic acids or peptides on beads, gels, polymer surfaces, fibers such as optical fibers, glass, or any other suitable substrate. Arrays can be packaged in ways that allow for diagnostic or other manipulation of a fully functional device.

[0013] A "microarray" is a hybridization array element arranged in an ordered manner on a matrix, such as a polynucleotide probe (e.g., an oligonucleotide) or a binder (e.g., an antibody). The matrix can be a solid matrix, such as a glass or silica slide, beads, fiber optic adhesive, or a semi-solid matrix, such as a nitrocellulose membrane. The nucleotide sequence can be DNA, RNA, or any arrangement thereof.

[0014] In this invention, the "nucleic acid membrane strip" includes a substrate and an oligonucleotide probe immobilized on the substrate; the substrate can be any substrate suitable for immobilizing oligonucleotide probes, including nylon membrane, nitrocellulose membrane, polypropylene membrane, glass slide, silicone wafer, micro-magnetic beads, but is not limited thereto.

[0015] In some embodiments, the chip includes probes or primers.

[0016] Furthermore, the chip includes at least one of microfluidic chip, microarray chip, fiber optic microbead chip, liquid phase chip, and in-situ synthesis chip.

[0017] Furthermore, the chip is a microfluidic chip.

[0018] In this invention, the term "microfluidic chip" refers to a chip that can manipulate microfluidics on a chip to carry out various functions of conventional physical, chemical or biological experiments. The channel size on the chip can be on the order of micrometers (μm) or even nanometers (nm).

[0019] In the context of this invention, the term "sample to be tested" as used refers to a composition obtained from or derived from a subject (e.g., an individual of interest) that contains cells and / or other molecular entities to be characterized and / or identified based on, for example, physical, biochemical, chemical, and / or physiological characteristics. For example, a sample refers to any sample derived from a subject of interest that is expected or known to contain cells and / or molecular entities to be characterized.

[0020] In the context of this invention, a subject refers to any individual of interest, preferably a living organism that may have high myopia, including humans, other mammals, preferably primates, and particularly preferably adolescents.

[0021] In some embodiments, the sample to be tested includes nucleic acids from the subject.

[0022] Furthermore, the sample was peripheral blood.

[0023] A third aspect of the present invention provides a method for constructing a high myopia risk model based on SNP locus genotypes. The method includes the following steps: obtaining equivalent spherical lens data of highly myopic individuals and non-highly myopic individuals, and constructing a high myopia risk model based on the SNP locus genotypes described in the first aspect using an algorithm.

[0024] In some embodiments, the methods for constructing the predictive model are known to those skilled in the art, and the steps of associating SNP locus genotypes with a certain probability or risk can be implemented and realized in different ways. Preferably, the SNP locus genotype is mathematically associated with the fundamental issue of high myopia risk. The determination of SNP locus genotypes can be combined with other clinical characteristics using any suitable existing technical mathematical methods, and a predictive model can be constructed using machine learning algorithms.

[0025] The machine learning includes algorithmic models developed using various development tools; these tools include one or more of TensorFlow, Scikit-Learn, PyTorch, OpenNN, RapidMiner, Azure Machine Learning, Apache Mahout, Shogun, KNIME, Vertex AI, H2Oai, Anaconda, Keras, Tableau, Fast.ai, Catalyst, Amazon ML, MLJAR, and Spell. The algorithmic models include one or more of convolutional neural networks, autoencoders, deep belief networks, linear regression, logistic regression, Lasso regression, Ridge regression, linear discriminant analysis, K-nearest neighbors, decision trees, perceptrons, support vector machines, ensemble learning, correlation analysis, Naive Bayes, AdaBoost, GBDT, XGBoost, LightGBM, CatBoost, or random forests.

[0026] A fourth aspect of the present invention provides a system for assessing the risk of high myopia based on axial length, the system comprising the following modules: The acquisition module is configured to acquire the SNP locus genotype data described in the first aspect in the sample; The processing module is configured to input the SNP locus genotype data from the sample as described in the first aspect into the high myopia risk model constructed by the method described in the third aspect for analysis, and obtain the analysis results. The output module is configured to output analysis results.

[0027] It should be understood that the systems, devices, and methods described in this invention can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0028] The fifth aspect of the present invention provides a computer device for assessing the risk of high myopia, the computer device including a memory and a processor, the memory for storing computer programs; The processor executes a computer program, which, when executed, implements the following method: Data is acquired to obtain the SNP locus genotype data described in the first aspect in the sample; The data is processed to input the SNP locus genotype data from the first aspect of the sample into the high myopia risk model constructed by the method described in the third aspect for analysis, and to obtain the analysis results. Output results, used to output analysis results.

[0029] The processor can also be called a Central Processing Unit (CPU). A processor may be an integrated circuit chip with signal processing capabilities. A processor can also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor can be a microprocessor or any conventional processor.

[0030] A sixth aspect of the present invention provides a computer program product, including a computer program for assessing the risk of high myopia, wherein the computer program, when executed by a processor, implements the following method: Data is acquired to obtain the SNP locus genotype data described in the first aspect in the sample; The data is processed to input the SNP locus genotype data from the first aspect of the sample into the high myopia risk model constructed by the method described in the third aspect for analysis, and to obtain the analysis results. Output results, used to output analysis results.

[0031] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, the functional units in the various embodiments of this invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0032] The seventh aspect of this invention provides the application of the reagent kit described in the first aspect, the high myopia risk model constructed by the method described in the third aspect, the system described in the fourth aspect, the computer device described in the fifth aspect, and / or the computer program product described in the sixth aspect in the preparation of high myopia risk assessment products.

[0033] Advantages and benefits of this invention: This invention provides a set of SNP locus biomarkers based on equivalent spherical lens for the prediction and assessment of high myopia risk. For the first time, rs10045697 was discovered as the SNP locus with the largest difference in equivalent spherical lens between high and non-high myopia individuals. SNP locus biomarkers containing this locus can provide an effective tool for early screening, early diagnosis, and precise intervention in clinical practice. Attached Figure Description

[0034] Figure 1 Manhattan plot of key site PDE6Ars10045697 found in a high myopia dataset.

[0035] Figure 2 The ROC curves are calculated for different thresholds of the filter set, where A is -10 D, B is -11 D, and C is -12 D.

[0036] Figure 3 The ROC curves were calculated for different thresholds on the validation set, where A is -10 D, B is -11 D, and C is -12 D.

[0037] Figure 4 The graph shows the ROC curves calculated for different thresholds in the sampled set, where A is -10 D, B is -11 D, and C is -12 D.

[0038] Figure 5 The graph shows the ROC curves calculated for different thresholds on the validation set after sampling, where A is -10 D, B is -11 D, and C is -12 D. Detailed Implementation

[0039] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0040] Example I. Experimental Methods 1. Study Design and Participants: Participants in this study were from the Myopia-Related Genetics and Intervention Consortium (MAGIC) project. Some patients underwent ophthalmological examinations, including refractive error measurements and ocular biometrics. Subsequent analyses in this study used only spherical equivalent (SE) as the primary endpoint. High myopia was defined based on the worst-case refractive state (WSE ≤ 1000 lb). 6.00 D). This study was approved by the Eye Hospital of Wenzhou Medical University and conducted in accordance with the principles of the Declaration of Helsinki. All participants provided written informed consent.

[0041] 2. Exclusion Criteria: Individuals lacking valid identification or SE (Self-Expression) were excluded during the initial phase of data processing. Participants who had previously undergone ophthalmic surgery were excluded. Additionally, participants were excluded if their worst-case refractive state was greater than -6.00 diopters (D).

[0042] 3. Genotypic Data and Quality Control: Genotypic data were retrieved from the patient database collected by the MAGIC project and variant filtering was performed using a standardized pipeline. Then, the corresponding genotypes for the five ocular phenotypes were extracted. Second-stage variant level quality control included the following exclusion steps: recall <90%, Hardy-Weinberg equilibrium p <1×10⁻⁶. 6 The minor allele frequency (MAF) is <0.01.

[0043] 4. Biomarker Screening and Validation: The collected patient samples were randomly divided into two high myopia datasets (equivalent spherical lens ≤ -6.0D), serving as a screening set and a validation set. The screening set was used to obtain SNP loci, while the validation set was not involved in any quality control parameter setting, SNP screening, or model construction process. Based on the difference in equivalent spherical lens, 82 SNP loci were identified in the screening set, with rs10045697 being the key locus.

[0044] For the combination of 82 SNP loci, the inventors calculated AUC values ​​at three equivalent spherical lens thresholds (-10D, -11D, and -12D) that are generally considered to be key in the art for high myopia, and also calculated AUC values ​​in the validation set to measure the efficacy of the combination in diagnosing common high myopia and very high myopia.

[0045] Because the original dataset had a severely imbalanced ratio of cases to controls, we further randomized the case and control groups to a 1:1 ratio and recalculated the AUC on the sampled dataset. The results showed that the AUC after sampling was highly consistent with the calculated result from the original dataset, indicating robustness of the analysis.

[0046] 5. Statistical analysis: Data are expressed as mean ± standard error.

[0047] II. Experimental Results 1. Participant Demographics: Ocular parameters of the participants were statistically analyzed, with spherical equivalent (SE) used as the primary study indicator. After applying quality control procedures, a total of 3474 participants were included in the final analysis.

[0048] In a single-phenotype GWAS analysis, a significant variant, PDE6Ars10045697, was identified under significance-level screening conditions. This locus achieved genome-wide suggestive significance in association analysis with SE (p = 7.476 × 10⁻⁶). -8 This accounts for 0.81% of the heritability of SE (sepsis 10045697). rs10045697 is a novel SNP based on SE and associated with high myopia. SE is a quantitative trait indicating the severity of myopia, and its genetic relationship has not been previously reported. Figure 1 As shown, the wild-type genotype (CC) of PDE6Ars10045697 was the most prevalent in the cohort (91.42%). Heterozygous genotype (CT) was present in 8.32% of individuals, while homozygous genotype (TT) was rare, occurring in 0.26%. Compared to CC genotype carriers, after adjusting for sex and age, SE was reduced by -0.48 D in CT genotype carriers and by -1.27 D in TT genotype carriers (P<0.0001), suggesting that the T allele of PDE6Ars10045697 may be associated with an increased risk of high myopia (Table 1).

[0049] Based on this, candidate genetic locus combinations were constructed with rs10045697 as the core, and receiver operating characteristic (ROC) curve analysis was performed on the locus combinations in the equivalent spherical lens screening set and the validation set, respectively. The area under the curve (AUC) was calculated to evaluate its predictive ability for the reduction of equivalent spherical lens and the risk of high myopia, thereby verifying the identification efficacy of the key locus combinations.

[0050] Table 1. Genotype Statistics

[0051] 2. Biomarker screening and verification The basic data of the selected samples are shown in Table 2. A total of 82 SNP combinations were obtained through screening, and their information is shown in Table 3.

[0052] Table 2. Statistics of the Filter Set Data

[0053] Table 3. SNP locus information table

[0054] The efficacy of SNP site combinations in diagnosing high myopia of different severity was verified using a validation set with different thresholds for equivalent spherical lens. The validation set sample data is shown in Table 4.

[0055] Table 4. Validation set data statistics

[0056] The AUC obtained for different thresholds in the two datasets are shown in Table 5. Figure 2-3 As shown in Table 3, the SNP locus combinations exhibit good diagnostic efficacy in high myopia of varying severity.

[0057] Table 5. AUC of the original dataset

[0058] 3. Sampling and testing ensure the versatility of the markers. To ensure the generalizability and external validity of the high myopia risk markers identified based on equivalent spherical lenses, a 1:1 random sampling was performed on the case and control groups in the original dataset, and the AUC was recalculated on the sampled dataset. Specifically, an equal number of samples were randomly selected from all high myopia cases to construct a balanced analysis cohort, avoiding overestimation or bias in model performance due to class imbalance. Both datasets were derived from the same population and constructed using a unified random sampling framework, thereby controlling for confounding factors while maximizing population representativeness. The selected set (Table 6) and validation set (Table 7) data after random sampling are shown in the following tables.

[0059] Table 6. Statistics of the selected set after sampling

[0060] Table 7. Statistics of the Validation Set Data after Sampling

[0061] Refit the dataset on the sampled dataset and calculate the area under the receiver operating characteristic (AUC). The AUCs after sampling are shown in Table 8. Figure 4-5 As shown in Table 3, the SNP markers exhibit stable discriminative ability under a balanced sample structure, without significant overfitting. This result not only verifies the reliability of the markers themselves but also demonstrates that the analytical framework constructed through random sampling effectively improves the generalizability of the model in the target population.

[0062] Table 8. AUC of the sampled dataset

[0063] The above description of the embodiments is only for understanding the method and core ideas of the present invention. It should be noted that those skilled in the art can make various improvements and modifications to the present invention without departing from the principles of the invention, and these improvements and modifications will also fall within the protection scope of the claims of the present invention.

Claims

1. A reagent kit for detecting the risk and susceptibility to high myopia, characterized in that, The kit includes reagents for detecting SNP locus genotypes, wherein the SNP locus genotypes are: rs10045697: C>T, rs72658579: T>C, rs61729970: C>T, rs147091881: G>A, rs12030: T>C, rs78587889: G>A, rs144389163: A>G, rs62621412: G>C, rs59454556: A>C, rs10489177: T>G, rs9787172: C>T, rs77113266: T>A, rs147783371: G>A, rs2028382: A>C, rs1156 8351: G>C, rs117179004: G>A, rs4067: A>G, rs2279321: G>A, rs2279322: C >T, rs544122500: G>A, rs78263747: C>A, rs139530035: G>A, rs17740066: G >A, rs1062293: A>G, rs78351985: A>G, rs9379657: G>A, rs78611987: T>C, r s9473132: G>A, rs9395287: G>A, rs34460237: G>A, rs146553037: G>T, rs19 5843: T>C, rs195812: G>T, rs73046334: T>C, rs6888: A>G, rs2286206: T>C , rs12671595: C>T, rs17214: A>C, rs11550100: T>C, rs74548386: A>G, rs18 32313: C>T, rs1974081: A>G, rs17158594: A>C, rs185112369: C>T, rs35083 184: A>T, rs12799381: G>A, rs622082: A>G, rs546382: C>T, rs488792: T>G, rs568862: A>G, rs10793024: A>T, rs2298573: T>C, rs17860556: G>A, rs135 6428: A>T, rs143519923: G>A, rs76415576: G>A, rs79983883: C>A, rs45613 639: A>G, rs17015438: T>G, rs2468245: C>T, rs45468703: T>C, rs2468222: G>A, rs34623199: G>A, rs78569455: G>C, rs798792: C>A, rs60214396: C>T,The combination of rs199816463: A>G, rs190278786: C>T, rs887387: T>C, rs11567842: A>G, rs3736238: C>T, rs758596: G>A, rs55880609: G>A, rs3744003: C>T, rs3753: T>C, rs7230037: G>A, rs572634: A>C, rs2303014: A>G, rs471979: G>C, rs6135048: C>A, rs1051415: C>T, rs2747565: G>A.

2. The reagent kit according to claim 1, characterized in that, The reagents include those used to detect the genotype of the SNP locus by TaqMan probe method, sequencing method, microarray method, mass spectrometry of flight, restriction fragment length polymorphism method, single strand conformation polymorphism method, allele-specific PCR, SNaPshot method, SNPlex method, denaturing high performance liquid chromatography or denaturing gradient gel electrophoresis.

3. The reagent kit according to claim 1, characterized in that, The kit also includes one or more of the following: reagents for collecting and processing subject samples, standards, calibrators, buffer solutions, and instructions.

4. The application of the reagent for detecting the SNP locus genotype of claim 1 in a test sample in the preparation of products for assessing the risk of high myopia, characterized in that, The products include reagent kits, chips, nucleic acid membrane strips, systems, devices, and storage media.

5. The application according to claim 4, characterized in that, The test sample includes nucleic acids from the subject.

6. A method for constructing a high myopia risk model based on SNP locus genotype, characterized in that, The method includes the following steps: obtaining equivalent spherical lens data for highly myopic individuals and non-highly myopic individuals, and constructing a high myopia risk model based on the SNP locus genotype described in claim 1 using an algorithm.

7. A system for assessing the risk of high myopia based on axial length, characterized in that, The system includes the following modules: The acquisition module is configured to acquire the SNP locus genotype data as described in claim 1 from the sample; The processing module is configured to input the SNP locus genotype data of claim 1 in the sample into the high myopia risk model constructed by the method described in any one of claims 6 for analysis, and obtain the analysis results; The output module is configured to output analysis results.

8. A computer device for assessing the risk of high myopia, characterized in that, The computer device includes a memory and a processor, the memory being used to store computer programs; The processor executes a computer program, which, when executed, implements the following method: Data is acquired to obtain the SNP locus genotype data as described in claim 1 in the sample; The data is processed to input the SNP locus genotype data of claim 1 in the sample into the high myopia risk model constructed by the method described in any one of claims 6 for analysis, and to obtain the analysis results; Output results, used to output analysis results.

9. A computer program product comprising a computer program for assessing the risk of high myopia, characterized in that, When this computer program is executed by the processor, it implements the following method: Data is acquired to obtain the SNP locus genotype data as described in claim 1 in the sample; The data is processed to input the SNP locus genotype data of claim 1 in the sample into the high myopia risk model constructed by the method described in claim 6 for analysis, and to obtain the analysis results. Output results, used to output analysis results.

10. The use of the kit according to any one of claims 1-3, the high myopia risk model constructed by the method of claim 6, the system according to claim 7, the computer device according to claim 8, and / or the computer program product according to claim 9 in the preparation of a high myopia risk assessment product.

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